Implementasi Agentic Artificial Intelligence dalam Sistem Pendukung Keputusan Kelayakan Ekspor pada PT. Caly Beta Sukses

Authors

  • Haikal Ayman Mumtaz Universitas Negeri Surabaya, Jawa Timur, Indonesia
  • Riska Dhenabayu Universitas Negeri Surabaya, Jawa Timur, Indonesia
  • Dhiyan Septa Wihara Universitas Negeri Surabaya, Jawa Timur, Indonesia
  • Achmad Fitro Universitas Negeri Surabaya, Jawa Timur, Indonesia

DOI:

https://doi.org/10.38035/jemsi.v7i6.9003

Keywords:

Artificial Intelligence, Analisis Kelayakan Ekspor, Sistem Pendukung Keputusan, UMKM, Design Science Research

Abstract

Proses pengambilan keputusan ekspor pada UMKM sering menghadapi berbagai kendala, seperti penentuan negara tujuan ekspor, perbedaan regulasi perdagangan, ketentuan Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), biaya pengiriman, serta analisis kelayakan ekspor yang masih dilakukan secara manual. Penelitian ini bertujuan untuk mengembangkan sistem analisis kelayakan ekspor berbasis Artificial Intelligence pada PT Caly Beta Sukses guna mendukung proses pengambilan keputusan ekspor secara lebih cepat dan terstruktur. Penelitian menggunakan metode Design Science Research yang terdiri atas tahap identifikasi permasalahan dan motivasi, penentuan tujuan solusi, perancangan dan pengembangan, demonstrasi, evaluasi, dan komunikasi. Sistem dikembangkan menggunakan web, platform n8n, Google Spreadsheet, OpenAI API, dan Microsoft Excel. Hasil penelitian menunjukkan bahwa sistem mampu mengintegrasikan data produk, negara tujuan ekspor, biaya pengiriman, regulasi perdagangan, dan ketentuan CITES dalam satu proses analisis. Hasil evaluasi menggunakan User Acceptance Testing menunjukkan bahwa seluruh skenario pengujian memperoleh hasil valid dengan tingkat keberhasilan sebesar 100%. Dengan demikian, sistem yang dikembangkan mampu membantu proses analisis kelayakan ekspor secara lebih efektif, efisien, dan berbasis data.

References

Awa, H. O., Ojiabo, O. U., & Orokor, L. E. (2017). Integrated technology-organization-environment (T-O-E) taxonomies for technology adoption. Journal of Enterprise Information Management, 30(6), 893–921. https://doi.org/10.1108/JEIM-03-2016-0079

C. E. (2020). Influence of artificial intelligence (AI) on firm performance: the business value of AI-based transformation projects. Business Process Management Journal, 26(7), 1893–1924. https://doi.org/10.1108/BPMJ-10-2019-0411

Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165–1188. https://doi.org/10.2307/41703503

Dumas, M., La Rosa, M., Mendling, J., & Reijers, H. A. (2018). Fundamentals of Business Process Management. Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-56509-4

Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., … Williams, M. D. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994. https://doi.org/10.1016/j.ijinfomgt.2019.08.002

Elia, S., Giuffrida, M., Mariani, M. M., & Bresciani, S. (2021). Resources and digital export: An RBV perspective on the role of digital technologies and capabilities in cross-border e-commerce. Journal of Business Research, 132, 158–169. https://doi.org/10.1016/j.jbusres.2021.04.010

Enholm, I. M., Papagiannidis, E., Mikalef, P., & Krogstie, J. (2022). Artificial Intelligence and Business Value: a Literature Review. Information Systems Frontiers, 24(5), 1709–1734. https://doi.org/10.1007/s10796-021-10186-w

Gill, P., Stewart, K., Treasure, E., & Chadwick, B. (2008). Methods of data collection in qualitative research: interviews and focus groups. British Dental Journal, 204(6), 291–295. https://doi.org/10.1038/bdj.2008.192

Kraus, S., Jones, P., Kailer, N., Weinmann, A., Chaparro-Banegas, N., & Roig-Tierno, N. (2021). Digital Transformation: An Overview of the Current State of the Art of Research. Sage Open, 11(3). https://doi.org/10.1177/21582440211047576

Linda, M., & Imbar, R. V. (2024). Perancangan Model Referral dengan Pendekatan Design Science Research Methodology. JuTISI (Jurnal Teknik Informatika Dan Sistem Informasi), 10(3), 430–438. https://doi.org/10.28932/jutisi.v10i3.9215

Mariani, M. M., Machado, I., Magrelli, V., & Dwivedi, Y. K. (2023). Artificial intelligence in innovation research: A systematic review, conceptual framework, and future research directions. Technovation, 122, 102623. https://doi.org/10.1016/j.technovation.2022.102623

Mikalef, P., & Gupta, M. (2021). Artificial intelligence capability: Conceptualization, measurement calibration, and empirical study on its impact on organizational creativity and firm performance. Information & Management, 58(3), 103434. https://doi.org/10.1016/j.im.2021.103434

Mira Orisa, Ahmad Faisol, & Mochammad Ibrahim Ashari. (2023). PERANCANGAN WEBSITE COMPANY PROFILE MENGGUNAKAN DESIGN SCIENCE

RESEARCH METHODOLOGY (DSRM). Jurnal Informatika Teknologi Dan Sains, 5(1), 160–164. https://doi.org/10.51401/jinteks.v5i1.2576

Nambisan, S., Wright, M., & Feldman, M. (2019). The digital transformation of innovation and entrepreneurship: Progress, challenges and key themes. Research Policy, 48(8), 103773. https://doi.org/10.1016/j.respol.2019.03.018

Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A Design Science Research Methodology for Information Systems Research. Journal of Management Information Systems, 24(3), 45–77. https://doi.org/10.2753/MIS0742-1222240302

Perifanis, N.-A., & Kitsios, F. (2023). Investigating the Influence of Artificial Intelligence on Business Value in the Digital Era of Strategy: A Literature Review. Information, 14(2), 85. https://doi.org/10.3390/info14020085

Pressman, R. S., & Maxim, B. R. (2020). Software Engineering: A Practitioner’s Approach (9th ed.). McGraw-Hill.

Raisch, S., & Krakowski, S. (2021). Artificial Intelligence and Management: The Automation–Augmentation Paradox. Academy of Management Review, 46(1), 192–210. https://doi.org/10.5465/amr.2018.0072

Russell, S., & Norvig, P. (2021). Artificial Intelligence: A Modern Approach (4th ed.). Pearson. Shrestha, Y. R., Ben-Menahem, S. M., & von Krogh, G. (2019). Organizational Decision-Making Structures in the Age of Artificial Intelligence. California Management Review, 61(4), 66–83. https://doi.org/10.1177/0008125619862257

Tambunan, T. (2019). Recent evidence of the development of micro, small and medium enterprises in Indonesia. Journal of Global Entrepreneurship Research, 9(1), 18. https://doi.org/10.1186/s40497-018-0140-4

Turban, E., Sharda, R., Delen, D., & King, D. (2011). Business Intelligence: A Managerial Approach (2nd ed.). Pearson.

Verhoef, P. C., Broekhuizen, T., Bart, Y., Bhattacharya, A., Qi Dong, J., Fabian, N., & Haenlein, M. (2021). Digital transformation: A multidisciplinary reflection and research agenda. Journal of Business Research, 122, 889–901. https://doi.org/10.1016/j.jbusres.2019.09.022

Vial, G. (2019). Understanding digital transformation: A review and a research agenda. The Journal of Strategic Information Systems, 28(2), 118–144. https://doi.org/10.1016/j.jsis.2019.01.003

Wamba-Taguimdje, S.-L., Fosso Wamba, S., Kala Kamdjoug, J. R., & Tchatchouang Wanko,

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Published

2026-07-21

How to Cite

Mumtaz, H. A., Dhenabayu, R., Wihara, D. S., & Fitro, A. (2026). Implementasi Agentic Artificial Intelligence dalam Sistem Pendukung Keputusan Kelayakan Ekspor pada PT. Caly Beta Sukses. Jurnal Ekonomi Manajemen Sistem Informasi, 7(6), 5260–5271. https://doi.org/10.38035/jemsi.v7i6.9003

Issue

Vol. 7 No. 6 (2026): Jurnal Ekonomi Manajemen Sistem Informasi (Juli - Agustus 2026)

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Articles

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Copyright (c) 2026 Haikal Ayman Mumtaz, Riska Dhenabayu, Dhiyan Septa Wihara, Achmad Fitro

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